def __init__(self, *args, attrmap=None, **kwargs):
super().__init__(**kwargs)
self.attrmap = attrmap
self.trajectory = Trajectory()
self.dumpattrs = {}
self.dumpfiles = list(flatten([glob(f) for f in args[0].split()]))
if len(self.dumpfiles) == 0:
raise ValueError('No dump file specified.')
self.read()
class DUMPReader(StructureIO):
"""Class for reading `LAMMPS dump` file format.
Parameters
----------
*args : :class:`~python:list`
:class:`~python:list` of one or more LAMMPS dump files.
attrmap : class:`~python:dict`
Python :class:`~python:dict` mapping custom dump attributes
to :class:`~sknano.core.atoms.Atom` attributes.
Examples
--------
Using LAMMPS, one often saves molecular dynamics atom trajectories
to one or more custom dump files containing per-atom attributes of
of each atom at a given timestep. Often the per-atom attributes
are calculated from custom LAMMPS compute commands that one may
want to map to a specific :class:`~sknano.core.atoms.Atom`
attribute.
For example, consider a dump file containing per-atom dump attributes
*id*, *mol*, *type*, *x*, *y*, *z*, *vx*, *vy*, *vz*, *c_atom_ke*,
*c_atom_pe*, and *c_atom_CN*, where *c_atom_ke*, *c_atom_pe*, and
*c_atom_CN* are the LAMMPS *compute-IDs* from custom compute commands
in a LAMMPS input script, which calculate per-atom values for
kinetic energy, potential energy, and coordination number, respectively.
To map these compute-IDs to corresponding
:class:`~sknano.core.atoms.Atom` attributes
:attr:`~sknano.core.atom.EnergyAtom.ke`,
:attr:`~sknano.core.atom.EnergyAtom.pe`,
and :attr:`~sknano.core.atom.CNAtom.CN`), respectively, one
would use the following :class:`~python:dict` mapping::
>>> from sknano.io import DUMPReader
>>> compute_attrmap = {'c_atom_pe': 'pe', 'c_atom_ke': 'ke',
... 'c_atom_CN': 'CN'}
>>> dumps = DUMPReader('dump.*', attrmap=compute_attrmap)
>>> print(repr(dumps.dumpattrs2str()))
'id mol type x y z vx vy vz c_atom_ke c_atom_pe c_atom_CN'
>>> print(repr(dumps.atomattrs2str()))
'id mol type x y z vx vy vz ke pe CN'
"""
def __init__(self, *args, attrmap=None, **kwargs):
super().__init__(**kwargs)
self.attrmap = attrmap
self.trajectory = Trajectory()
self.dumpattrs = {}
self.dumpfiles = list(flatten([glob(f) for f in args[0].split()]))
if len(self.dumpfiles) == 0:
raise ValueError('No dump file specified.')
self.read()
def __getattr__(self, name):
try:
return getattr(self.trajectory, name)
except AttributeError:
return super().__getattr__(name)
def __iter__(self):
return iter(self.trajectory)
def __getitem__(self, index):
return self.trajectory[index]
def read(self):
"""Read all snapshots from each dump file."""
for dumpfile in self.dumpfiles:
with zopen(dumpfile) as f:
snapshot = self.read_snapshot(f)
while snapshot is not None:
self.trajectory.append(snapshot)
print(snapshot.timestep, end=' ')
sys.stdout.flush()
snapshot = self.read_snapshot(f)
print()
self.trajectory.sort(key=attrgetter('timestep'))
self.trajectory.cull()
print("read {:d} snapshots".format(self.Nsnaps))
self.trajectory.time_selection.all()
self.trajectory.t0_snapshot = self.trajectory[0]
if self.dumpattrs:
print('Dumped Atom attributes: {}'.format(self.dumpattrs2str()))
else:
print('No dump column assignments')
if 'x' not in self.dumpattrs or 'y' not in self.dumpattrs or \
'z' not in self.dumpattrs:
print('dump scaling status unknown')
elif self.Nsnaps > 0:
if self.scale_original:
self.unscale()
elif self.scale_original is None:
print('dump scaling status unknown')
else:
print('dump is already unscaled')
def read_snapshot(self, f):
try:
snapshot = Snapshot(self.trajectory)
f.readline()
snapshot.timestep = int(f.readline().strip().split()[0])
f.readline()
snapshot.Natoms = int(f.readline().strip())
snapshot.atom_selection = np.zeros(snapshot.Natoms, dtype=bool)
item = f.readline().strip()
try:
snapshot.boxstr = item.split('BOUNDS')[1].strip()
except IndexError:
snapshot.boxstr = ''
snapshot.triclinic = False
snapshot.bounding_box = Cuboid()
if 'xy' in snapshot.boxstr:
snapshot.triclinic = True
for dim, tilt_factor in zip(('x', 'y', 'z'), ('xy', 'xz', 'yz')):
bounds = f.readline().strip().split()
setattr(snapshot, dim + 'lo', float(bounds[0]))
setattr(snapshot, dim + 'hi', float(bounds[1]))
setattr(snapshot.bounding_box, dim + 'min',
getattr(snapshot, dim + 'lo'))
setattr(snapshot.bounding_box, dim + 'max',
getattr(snapshot, dim + 'hi'))
try:
setattr(snapshot, tilt_factor, float(bounds[2]))
except IndexError:
setattr(snapshot, tilt_factor, 0.0)
if not self.dumpattrs:
xflag = yflag = zflag = None
attrs = f.readline().strip().split()[2:]
for i, attr in enumerate(attrs):
if attr in ('x', 'xu', 'xs', 'xsu'):
self.dumpattrs['x'] = i
if attr in ('x', 'xu'):
xflag = False
else:
xflag = True
elif attr in ('y', 'yu', 'ys', 'ysu'):
self.dumpattrs['y'] = i
if attr in ('y', 'yu'):
yflag = False
else:
yflag = True
elif attr in ('z', 'zu', 'zs', 'zsu'):
self.dumpattrs['z'] = i
if attr in ('z', 'zu'):
zflag = False
else:
zflag = True
else:
self.dumpattrs[attr] = i
self.scale_original = None
if all([flag is False for flag in (xflag, yflag, zflag)]):
self.scale_original = False
if all([flag for flag in (xflag, yflag, zflag)]):
self.scale_original = True
self.atomattrs = \
sorted(self.dumpattrs, key=self.dumpattrs.__getitem__)
self.attr_dtypes = [attr_dtypes[attr] if attr in attr_dtypes
else float for attr in self.atomattrs]
if self.attrmap is not None:
self.remap_atomattr_names(self.attrmap)
self.attrmap = None
self.unknown_attrs = \
{attr: self.atomattrs.index(attr) for
attr in set(self.atomattrs) - set(dir(Atom()))}
[self.atomattrs.remove(attr) for attr in self.unknown_attrs]
else:
f.readline()
snapshot.atomattrs = self.atomattrs
snapshot.attr_dtypes = self.attr_dtypes
atoms = \
np.zeros((snapshot.Natoms, len(self.atomattrs)), dtype=float)
for n in range(snapshot.Natoms):
line = [float(value) for col, value in
enumerate(f.readline().strip().split())
if col not in self.unknown_attrs.values()]
atoms[n] = line
snapshot.atoms = atoms
return snapshot
except IndexError:
return None
def remap_atomattr_names(self, attrmap):
"""Rename attributes in the :attr:`DUMPReader.atomattrs` list.
Parameters
----------
attrmap : :class:`~python:dict`
:class:`~python:dict` mapping atom attribute name to new
attribute name.
"""
for k, v in attrmap.items():
try:
self.atomattrs[self.atomattrs.index(k)] = v
except ValueError:
pass
def scale(self):
"""Scale cartesian coordinates to fractional coordinates."""
xi = self.dumpattrs['x']
yi = self.dumpattrs['y']
zi = self.dumpattrs['z']
for snapshot in self.trajectory:
atoms = snapshot.get_atoms(asarray=True)
if atoms is not None:
xlo = snapshot.xlo
xhi = snapshot.xhi
ylo = snapshot.ylo
yhi = snapshot.yhi
zlo = snapshot.zlo
zhi = snapshot.zhi
lx = xhi - xlo
ly = yhi - ylo
lz = zhi - zlo
xy = snapshot.xy
xz = snapshot.xz
yz = snapshot.yz
if np.allclose([xy, xz, yz], np.zeros(3)):
atoms[:, xi] = (atoms[:, xi] - snapshot.xlo) / lx
atoms[:, yi] = (atoms[:, yi] - snapshot.ylo) / ly
atoms[:, zi] = (atoms[:, zi] - snapshot.zlo) / lz
else:
xlo = xlo - min((0.0, xy, xz, xy + xz))
xhi = xhi - max((0.0, xy, xz, xy + xz))
lx = xhi - xlo
ylo = ylo - min((0.0, yz))
yhi = yhi - max((0.0, yz))
ly = yhi - ylo
atoms[:, xi] = (atoms[:, xi] - snapshot.xlo) / lx + \
(atoms[:, yi] - snapshot.ylo) * xy / (lx * ly) + \
(atoms[:, zi] - snapshot.zlo) * (yz * xy - ly * xz) / \
(lx * ly * lz)
atoms[:, yi] = (atoms[:, yi] - snapshot.ylo) / ly + \
(atoms[:, zi] - snapshot.zlo) * yz / (ly * lz)
atoms[:, zi] = (atoms[:, zi] - snapshot.zlo) / lz
def unscale(self):
"""Unscale fractional coordinates to cartesian coordinates."""
xi = self.dumpattrs['x']
yi = self.dumpattrs['y']
zi = self.dumpattrs['z']
for snapshot in self.trajectory:
atoms = snapshot.get_atoms(asarray=True)
if atoms is not None:
xlo = snapshot.xlo
xhi = snapshot.xhi
ylo = snapshot.ylo
yhi = snapshot.yhi
zlo = snapshot.zlo
zhi = snapshot.zhi
lx = xhi - xlo
ly = yhi - ylo
lz = zhi - zlo
xy = snapshot.xy
xz = snapshot.xz
yz = snapshot.yz
if np.allclose([xy, xz, yz], np.zeros(3)):
atoms[:, xi] = snapshot.xlo + atoms[:, xi] * lx
atoms[:, yi] = snapshot.ylo + atoms[:, yi] * ly
atoms[:, zi] = snapshot.zlo + atoms[:, zi] * lz
else:
xlo = xlo - min((0.0, xy, xz, xy + xz))
xhi = xhi - max((0.0, xy, xz, xy + xz))
lx = xhi - xlo
ylo = ylo - min((0.0, yz))
yhi = yhi - max((0.0, yz))
ly = yhi - ylo
atoms[:, xi] = snapshot.xlo + atoms[:, xi] * lx + \
atoms[:, yi] * xy + atoms[:, zi] * xz
atoms[:, yi] = snapshot.ylo + atoms[:, yi] * ly + \
atoms[:, zi] * yz
atoms[:, zi] = snapshot.zlo + atoms[:, zi] * lz
def atomattrs2str(self):
"""Return a space-separated string of parsed atom attributes."""
return ' '.join(self.atomattrs)
def dumpattrs2str(self):
"""Return a space-separated string of the dumped atom attributes."""
return ' '.join(sorted(self.dumpattrs, key=self.dumpattrs.__getitem__))
def test1():
traj = Trajectory()
assert_equal(traj.Nsnaps, 0)
print(traj)